使用机器学习的下一代网络钓鱼检测和预防系统

Somil Tyagi, Dr. Rajesh Kumar Tyagi, Dr. Pushan Kumar Dutta, Dr. Priyanka Dubey
{"title":"使用机器学习的下一代网络钓鱼检测和预防系统","authors":"Somil Tyagi, Dr. Rajesh Kumar Tyagi, Dr. Pushan Kumar Dutta, Dr. Priyanka Dubey","doi":"10.1109/ICAISC56366.2023.10085529","DOIUrl":null,"url":null,"abstract":"Phishing is one of the topmost social engineering attacks in which an attacker sends a luring email via fake email address, email content through which either they try to compromise the end-user account by stealing their account credentials simply like username and password or even more complex way is to compromise the user’s device by binding the malicious payload that could be virus, trojans, spyware and lot more within the email sent by the attacker to the victim. According to the APWG, phishing activity trends report found that the December 2021 stats shows that the number of phishing attacks was triple compared to the attacks in early 2020, this shows still phishing is still in the leading position in all of the cybercrimes happened or happening in today’s world. The phishing problem is still a major problem across the globe which affects society, work culture, and economic growth in industries as well, thus there is not any single solution with which one person or industry can fight the phishing attack. The objective of this research paper is to make a simple yet effective one-stop solution for phishing detection and prevention system using machine learning and making an intelligent web browser plugin and to study different machine learning models and approaches with which we can come up with an efficient product.","PeriodicalId":422888,"journal":{"name":"2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Next Generation Phishing Detection and Prevention System using Machine Learning\",\"authors\":\"Somil Tyagi, Dr. Rajesh Kumar Tyagi, Dr. Pushan Kumar Dutta, Dr. Priyanka Dubey\",\"doi\":\"10.1109/ICAISC56366.2023.10085529\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Phishing is one of the topmost social engineering attacks in which an attacker sends a luring email via fake email address, email content through which either they try to compromise the end-user account by stealing their account credentials simply like username and password or even more complex way is to compromise the user’s device by binding the malicious payload that could be virus, trojans, spyware and lot more within the email sent by the attacker to the victim. According to the APWG, phishing activity trends report found that the December 2021 stats shows that the number of phishing attacks was triple compared to the attacks in early 2020, this shows still phishing is still in the leading position in all of the cybercrimes happened or happening in today’s world. The phishing problem is still a major problem across the globe which affects society, work culture, and economic growth in industries as well, thus there is not any single solution with which one person or industry can fight the phishing attack. The objective of this research paper is to make a simple yet effective one-stop solution for phishing detection and prevention system using machine learning and making an intelligent web browser plugin and to study different machine learning models and approaches with which we can come up with an efficient product.\",\"PeriodicalId\":422888,\"journal\":{\"name\":\"2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAISC56366.2023.10085529\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAISC56366.2023.10085529","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

网络钓鱼是最重要的社会工程攻击之一,其中攻击者通过虚假的电子邮件地址发送诱人的电子邮件,电子邮件内容,通过这些电子邮件,他们要么试图通过窃取他们的帐户凭据来破坏最终用户帐户,就像用户名和密码一样,或者更复杂的方式是通过绑定恶意有效载荷来破坏用户的设备,恶意有效载荷可能是病毒,特洛伊木马,间谍软件和更多的攻击者发送给受害者的电子邮件。根据APWG,网络钓鱼活动趋势报告发现,2021年12月的统计数据显示,与2020年初的攻击相比,网络钓鱼攻击的数量增加了三倍,这表明网络钓鱼仍然在当今世界发生或正在发生的所有网络犯罪中处于领先地位。网络钓鱼问题仍然是全球范围内的一个主要问题,它影响着社会,工作文化和行业的经济增长,因此没有任何一个人或行业可以对抗网络钓鱼攻击的单一解决方案。本研究论文的目的是利用机器学习和制作智能web浏览器插件,为网络钓鱼检测和预防系统提供一个简单而有效的一站式解决方案,并研究不同的机器学习模型和方法,我们可以提出一个高效的产品。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Next Generation Phishing Detection and Prevention System using Machine Learning
Phishing is one of the topmost social engineering attacks in which an attacker sends a luring email via fake email address, email content through which either they try to compromise the end-user account by stealing their account credentials simply like username and password or even more complex way is to compromise the user’s device by binding the malicious payload that could be virus, trojans, spyware and lot more within the email sent by the attacker to the victim. According to the APWG, phishing activity trends report found that the December 2021 stats shows that the number of phishing attacks was triple compared to the attacks in early 2020, this shows still phishing is still in the leading position in all of the cybercrimes happened or happening in today’s world. The phishing problem is still a major problem across the globe which affects society, work culture, and economic growth in industries as well, thus there is not any single solution with which one person or industry can fight the phishing attack. The objective of this research paper is to make a simple yet effective one-stop solution for phishing detection and prevention system using machine learning and making an intelligent web browser plugin and to study different machine learning models and approaches with which we can come up with an efficient product.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信